comparison of different facts controllers and various...

CHAPTER – 3

COMPARISON OF DIFFERENT FACTS CONTROLLERS AND VARIOUS INPUT SIGNALS

CHAPTER-3

COMPARISON OF DIFFERENT FACTS CONTROLLERS AND VARIOUS INPUT SIGNALS

3.1 INTRODUCTION Damping of power system oscillation is one of the main concerns in the power

system operation since many years [62, 63]. In the recent years, the fast progress in

the field of power electronics have opened new opportunities for the application of

Flexible AC Transmission Systems (FACTS) devices as one of the most effective

ways to improve power system operation controllability and power transfer limits

[64, 65]. Due to the development of FACTS devices, Static Var Compensator (SVC),

Static Synchronous Compensator (STATCOM) and Static Synchronous Series

Compensator (SSSC) are routinely used in modern power systems. Hence, these

FACTS controllers are considered in this chapter for comparison of power oscillation

damping performance [2, 5, 7 ].

SVC and STATCOM are members of FACTS family that are connected in

shunt with the system [4, 6]. Even though the primary purpose of SVC and

STATCOM is to support bus voltage by injecting (or absorbing) reactive power, it is

also capable of improving the power system stability [66]. When a shunt compensator

is present in a power system to support the bus voltage, a supplementary damping

controller could be designed to modulate the bus voltage in order to improve damping

of system oscillations [21, 67]. SSSC is voltage sourced based series compensator and

provides the virtual compensation of transmission line impedance by injecting the

controllable voltage in series with the transmission line. The ability of SSSC to

operate in capacitive as well as inductive mode makes it very effective in controlling

the power flow of the system [8, 9]. An auxiliary stabilizing signal can also be

superimposed on the power flow control function of the SSSC so as to improve power

system oscillation stability [31]. Applications of SSSC for power oscillation damping,

stability enhancement and frequency stabilization can be found in several references

[28, 68-70]. The influence of degree of compensation and mode of operation of SSSC

ChapterChapterChapterChapter----3 : 3 : 3 : 3 : Comparison Comparison Comparison Comparison oooof Difff Difff Difff Different FACTS Controllers erent FACTS Controllers erent FACTS Controllers erent FACTS Controllers aaaand Various Input Signalsnd Various Input Signalsnd Various Input Signalsnd Various Input Signals

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on small disturbance and transient stability is also reported in the literature [71, 72].

Artificial intelligence-based approaches have been proposed recently to design a

FACTS-based supplementary damping controller. These approaches include Particle

Swarm Optimization [35, 73], Genetic Algorithm [21], Differential Evolution [36,

55], Multi-Objective Evolutionary Algorithm [74] etc.

In the design of an efficient and effective damping controller, selection of the

appropriate input signal is a primary issue. Input signal must give correct control

actions when a disturbance occurs in the power system. Most of the available

literatures on damping controller design are based on either local signal or remote

signal. Also the issues related to potential time delays due to sensor time constant and

signal transmission delays are hardly addressed in the literature. Despite significant

strides in the development of advanced control schemes over the past two decades, the

conventional lead–lag structure controller remains the controller’s of choice in many

industrial applications. The conventional lead–lag controller structure remains an

engineer’s preferred choice because of its structural simplicity, reliability and the

favorable ratio between performance and cost. Beyond these benefits, it also offers

simplified dynamic modeling, lower user-skill requirements and minimal

development effort, which are issues of substantial importance to engineering

practice. In view of the above, a lead–lag structure controller has been considered in

the present study to modulate the controller injected or applied voltage.

A number of conventional techniques have been reported in the literature

pertaining to design problems of lead-lag structure controller, namely the eigen value

assignment, mathematical programming, gradient procedure for optimization, and

also the modern control theory. Unfortunately, the conventional techniques are time

consuming as they are iterative and require heavy computation burden and slow

convergence. In addition, the search process is susceptible to be trapped in local

minima, and the solution obtained may not be optimal. The evolutionary methods

constitute an approach to search for the optimum solutions via some form of directed

random search process. A relevant characteristic of the evolutionary methods is that

they search for solutions without previous problem knowledge.


63

Recently, Gravitational search algorithm (GSA) appeared as a promising

evolutionary technique for handling the optimization problems [56]. GSA has been

popular in academia and the industry mainly because of its intuitiveness, ease of

implementation, and the ability to effectively solve highly nonlinear optimization

problems that are typical of complex engineering systems. It has been reported in the

literature that GSA is more efficient in terms of CPU time and offers higher precision

with more consistent results [37, 56]. In view of the above, this chapter proposes to

use GSA optimization technique for the damping controller design. In recent years,

the fast development of communication technology, low price communication devices

and various communication media makes it possible to provide the control center with

the real time signals from remote areas. However, the use of centralized controller

entails inputs that may arrive after a certain time delay. Time delays can make the

control system less effective. In order to satisfy specifications for wide-area control

systems, the design of a controller should take into account this time delay in order to

provide a controller that is robust, not only for the range of operating conditions

desired, but also for the uncertainty in delay. Recently there is a growing interest in

designing the controllers in the presence of uncertain time delays [75, 76, 77]. In view

of the above, this chapter investigates the design of various FACTS based damping

controller considering the potential time delays. Line active power as local signal and

speed deviation as remote signal are considered as candidate input signals for the

proposed FACTS based damping controllers. For controller design, Gravitational

Search Algorithm is employed due to its superior performance as presented in Chapter

2. To show the robustness of the proposed design approach, simulation results are

presented under various disturbance and faults for both SMIB and multi-machine

power system. Also, a comparison has been made between remote and local signal

and results are presented and analyzed.

The main objectives of the research work presented in this chapter are as follows:

1. To compare the damping performance of various FACTS controllers such as:

SVC, STATCOM and SSSC in a SMIB power system.

2. To investigate the effect of controller input signals (both local and remote) on

the performance of various FACTS based controller.


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3. To investigate the effect of potential time delays on the performance of

various FACTS based controller.

4. To design the FACTS based controller in a multi-machine power system.

3.2 SYSTEM UNDER STUDY

3.2.1 SMIB POWER SYSTEM WITH SVC AND STATCOM

The Single Machine Infinite Bus (SMIB) power system installed with a

SVC/STATCOM as shown in Fig. 3.1 is considered in this study. In Fig. 3.1, T1 and

T2 represents the main transformer and coupling transformer respectively, VT and VB

are the generator terminal and infinite-bus voltages, respectively, VSVC/STATCOM is the

bus voltages where shunt FACTS device is connected respectively, I is the line

current and PL and PL1 are the total real power flow in the transmission lines and that

in one line, respectively. The modeling of important power system components for

stability studies have already been given in Chapter 2. All the relevant parameters are

given in Appendix-II.

Load

STATCOMSVCV /TV

BV

Tr. lineT1

SVC/STATCOM

Generator

Bus-1Bus-2 Bus-3

ShuntFACTSDevices

T2

I PLPL1

Fig. 3.1 Single-machine infinite-bus power system with SVC/STATCOM


65

3.2.2 OVERVIEW OF SVC AND ITS CONTROL SYSTEM

SVC is basically a shunt connected Static Var Generator whose output is

adjusted to exchange capacitive or inductive current so as to maintain or control

specific power system variables. Fig. 3.2 shows the single-line diagram of a SVC and

a simplified block diagram of its control system.

The control system consists of [57]:

• A measurement system measuring the positive-sequence voltage to be

controlled.

• A voltage regulator that uses the voltage error (difference between the

measured voltage Vm and the reference voltage (Vref) to determine the SVC

susceptance needed to keep the system voltage constant.

• A distribution unit that determines the Thyristor Switched Capacitors (TSC)

and eventually Thyristor Switched Reactors (TSR) that must be switched in

and out, and computes the firing angle α of TCRs.

A synchronizing system using a Phase-Locked Loop (PLL) synchronized on the

secondary voltages and a pulse generator that send appropriate pulses to the thyristors.

VoltageMeasurement

Synchronizing Unit(PLL)

Pulse Generator

Distributionunit

VoltageRegulator∑

Pulse

TCR TSC

Primary voltage mV

refV

α

+−

Secondary voltage

Fig. 3.2 Single-line diagram of control system of SVC


66

3.2.3 OVERVIEW OF STATCOM AND ITS CONTROL SYSTEM

A Static Synchronous Compensator (STATCOM) is a controlled reactive-

power source. It provides voltage support by generating or absorbing reactive power

at the point of common coupling without the need of large external reactors or

capacitor banks [2]. The basic electronic block of a STATCOM is the Voltage

Sourced Converter (VSC), which in general converts an input dc voltage into a three-

phase output voltage at fundamental frequency, with rapidly controllable amplitude

and phase angle. In addition to this, the controller has a coupling transformer and a dc

capacitor. Fig. 3.3 shows the single-line diagram of a STATCOM and a simplified

block diagram of its control system. In Fig. 3.3, references fQ eR and fP eR define the

magnitude and phase angle of the converter voltage cnvV necessary to exchange the

desired reactive and active power between the solid state voltage sourced converter

and the ac system. If the device is operated strictly for reactive power exchange, fPRe

is set to zero and the external energy source is not required. The converter voltage

cnvV is in phase with the ac terminal voltage acV and there is practically no real power

flow from or to VSC (without energy storage). The STATCOM supplies reactive

power to the ac system if cnvV is greater than acV and consumes reactive power if cnvV

is lower than acV .The device can be designed to maintain the magnitude of the bus

voltage constant by controlling the magnitude and/or phase shift of the VSC output

voltage.

The control system consists of:

• A Phase-Locked Loop (PLL) to synchronize on the positive-sequence

component of the 3-phase primary voltage 1V . The direct-axis and quadrature-

axis components of the AC 3-phase voltage and currents (labeled as dV , qV and

dI , qI on the diagram) are computed using the output of the PLL.

• The measurement systems measuring the d-axis and q-axis components of AC

positive-sequence voltage and currents to be controlled as well as the DC

voltage DCV .


67

• The regulation loops, namely the AC voltage regulator and a DC voltage

regulator. The output of the AC voltage regulator and DC voltage regulator are

the reference current refqI and refdI , for the current regulator.

• An inner current regulation loop consisting of a current regulator, which

controls the magnitude and phase of the voltage generated by the PWM

converter.

AC VoltageMeasurement

AC VoltageRegulator∑

PLLCurrent

Measurement

acV

refV

1V

I

tωθ =

dq1V

qI

dI

DC VoltageMeasurement

DC VoltageRegulator∑

VoltageSourcedConvt.(VSC)

1V 2V

I

DCV

dcV

refdcV

PWMModulator

CurrentRegulator

∑

∑

θ

d2V

q2V

qI

dI

refqI

refdI

dq1V

+

−+

−

+−

+−

Fig. 3.3 Single-line diagram of control system of STATCOM

3.3 THE PROPOSED APPROACH

3.3.1 STRUCTURE OF PROPOSED SSSC, STATCOM AND SVC BASED DAMPING CONTROLLERS

Here lead–lag structured controller is considered as SVC, STATCOM and

SSSC-based damping controllers as shown in Figs. 3.4 and 3.5. The lead-lag structure

is preferred by the power system utilities because of the ease of on-line tuning and

also lack of assurance of the stability by some adaptive or variable structure

techniques. The structure consists of a delay block, a gain block with gain KS, a signal

washout block and two-stage phase compensation block. The time delay introduced

due to delay block depends on the type of input signal. For local input signals only the

sensor time constants is considered and for remote signals both sensor time constant


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and the signal transmission delays are included. The signal washout block serves as a

high-pass filter, with the time constant TW, high enough to allow signals associated

with oscillations in input signal to pass unchanged. From the viewpoint of the

washout function, the value of TW is not critical and may be in the range of 1 to 20

seconds [1]. The phase compensation blocks (time constants ST1 , ST2 and ST3 , ST4 )

provide the appropriate phase-lead characteristics to compensate for the phase lag

between input and the output signals. In Fig. 3.4, Vref represents the reference injected

or applied voltage as desired by the steady operation of the system. The steady state

loop acts quite slowly in practice and hence, in the present study Vref is assumed to be

constant during the disturbance period. The desired value of compensation is obtained

according to the change in the SSSC, SVC and STATCOM injected or applied

voltage ∆VSSSC/STATCOM/SVC which is added to Vref to get the desired VSSSC/STATCOM/SVC

SKW

WsT

sT

+1 S

SsT

sT

2

111++

S

SsT

sT

4

311++

Inputsignal Gain

BlockWashout

BlockTwo stage

lead-lag Block

Output

refSVCSTATCOMV _/

refV

++

max_/ refSVCSTATCOMV

∑D

Delay

SVCSTATCOMV /∆

min__/ refSVCSTATCOMV

Fig. 3. 4 Structure of the proposed SVC and STATCOM and based supplementary damping controller with time delay

SKW

WsT

sT

+1 S

SsT

sT

2

111++

S

SsT

sT

4

311++

Inputsignal Gain

BlockWashout

BlockTwo stage

lead-lag Block

Output

qV

qV

++

maxqV

∑D

Delay

Vsssc∆

minqV

Fig. 3. 5 Structure of the proposed SSSC based supplementary damping controller

with time delay

3.3.2 PROBLEM FORMULATION In the lead-lag structured controllers, the washout time constants TW is usually

pre-specified [1]. A washout time constant TW = 10s is used in the present study. The

controller gain SK and the time constants ST1 , ST2 , ST3 and ST4 are to be

determined for each cases. For the proposed shunt FACTS controllers STATCOM

and SVC, during steady state conditions ∆VSTATCOM/SVC and Vref are constant. During


69

dynamic conditions the reference voltage ∆VSTATCOM/SVC are modulated to damp

system oscillations. The effective reference voltage VSTATCOM/SVC_ref in dynamic

conditions is given by:

SVCSTATCOMefrrefSVCSTATCOM VVV /_/ ∆+= (3.1)

For the case of SSSC controller during steady state conditions ∆VSSSC and Vq

are constant. During dynamic conditions the injected voltage ∆VSSSC are modulated to

damp system oscillations. The effective injected voltage VSSSC in dynamic conditions

is given by:

SSSCqqSSSC VVV ∆+=_ (3.2)

In the design of a robust damping controller, selection of the appropriate

input signal is a main issue. Input signal must give correct control actions when a

disturbance occurs in the power system. Both local and remote signals can be used as

control. To avoid additional costs associated with communication and to improve

reliability, input signal should preferably be locally measurable. However, local

control signals, although easy to get, may not contain the desired oscillation modes.

So, compared to wide-area signals, they are not as highly controllable and observable.

Owing to the recent advances in optical fiber communication and global positioning

systems, the wide-area measurement system can realize phasor measurement

synchronously and deliver it to the control center even in real time, which makes the

wide-area signal a good alternative for control input. In a wide-area monitoring

system, global positioning system synchronized time-stamped data are used. In

today’s technology, dedicated communication channels should not have more than

50-ms delay for the transmission of measured signals even in the worst scenarios

[101]. For local input signals, line active power, line reactive power, line current

magnitude and bus voltage magnitudes are all candidates to be considered in the

selection of input signals for the FACTS power oscillation damping controller.

Among these possible local input signals, active power and current are the most

commonly employed in the literature. Similarly, generator rotor angle and speed

deviation can be used as remote signals. However rotor speed seems to be a better

alternative as input signal for FACTS based controller [102] In view of the above,


70

both line active power and speed deviations are considered and compared as candidate

input signals for the SSSC/STATCOM/SVC based controller. For local signals a

sensor time constant of 15 ms is considered. For remote signals a signal transmission

delay of 50 ms is considered along with the sensor time constant of 15 ms. In the

present study, an integral time absolute error of the speed deviations is taken as the

objective function J expressed as:

∫=

=

⋅⋅∆=simtt

t

dttJ0

|| ω (3.3)

Where, ∆ω is the speed deviation in and tsim is the time range of the simulation.

During normal operating condition there is complete balance between input

mechanical power and output electrical power and this is true for all operating points.

During disturbance, the balance is disturbed and the difference power enters

into/drawn from the rotor. Hence the rotor speed deviation and subsequently all other

parameters (power, current, voltage etc.) change. As the input to the SSSC/

STATCOM/ SVC based controller is the speed deviation/electrical power, the SSSC

injected voltage and STATCOM/SVC injected currents are suitable modulated and

the power balanced is maintained at the earliest time period irrespective of the

operating point. So, with the change in operating point also the SSSC/STATCOM/

SVC based controller parameters remain fixed.

For objective function calculation, the time-domain simulation of the power

system model is carried out for the simulation period. It is aimed to minimize this

objective function in order to improve the system response in terms of the settling

time and overshoots. The problem constraints are the SSSC/STATCOM/SVC

controller’s parameter bounds. Therefore, the design problem can be formulated as

the following optimization problem.

Minimize J (3.4)

Subject to

maxminSSS KKK ≤≤

max11

min1 SSS TTT ≤≤


71

max22

min2 SSS TTT ≤≤

max33

min3 SSS TTT ≤≤

max44

min4 SSS TTT ≤≤ .

3.4 RESULTS AND DISCUSSIONS

The behavior underlying the performance of a synchronous machine with the

excitation system, mechanical control system and installed FACTS controller etc., is

represented by a set of non-linear differential equations. Thus the complete

mathematical description of a power system becomes difficult to solve. To simplify

the computational burden, linearized models are used which gives satisfactory results

under small disturbance conditions. However, linear models cannot properly capture

complex dynamics of the system, especially during major disturbances. This presents

difficulties for tuning the FACTS controllers in that, the controllers tuned to provide

desired performance at small disturbance condition do not guarantee acceptable

performance in the event of major disturbances. The complete non-liner model of the

power system with FACTS can be developed in MATLAB/SIMULINK using the

inbuilt non-linear power system components or by developing the non-linear models

of some power system components. The SimPowerSystems (SPS) toolbox is used for

all simulations and SSSC-based damping controller design [57]. SPS is a MATLAB-

based modern design tool that allows scientists and engineers to rapidly and easily

build models to simulate power systems using SIMULINK environment. In order to

optimally tune the parameters of the SVC, STATCOM, SSSC-based damping

controllers as well as to assess its performance, the model of example power system

shown in Fig. 3.1 and 2.1 are developed using SPS blockset. The system consists of a

of 2100 MVA, 13.8 kV, 60 Hz hydraulic generating unit, connected to an infinite bus

through a 300 km long double-circuit transmission, 3-phase 13.8/500 kV step-up

transformer and a 100 MVA SSSC, 100MVAR SVC and 100MVA STATCOM. All

the relevant parameters are given in Appendix I & Appendix II. The model of the

system under study has been developed in MATLAB/SIMULINK environment and

GSA programme has been written in .m file. For objective function calculation, the

developed model is simulated in a separate programme (by another .m file using


72

initial population/controller parameters) considering a disturbance. Form the

SIMULINK model the objective function value is evaluated and moved to workspace.

The process is repeated for each individual in the population. The optimization of the

proposed SVC, STATCOM, SSSC-based damping controller parameters is carried out

by minimizing the objective function given in Eq. (3.3) employing GSA. The

objective function value is evaluated for each individual by simulating the example

power system, considering a severe disturbance. For objective function calculation, a

3-phase short-circuit fault in one of the parallel transmission lines is considered.The

flow chart of the GSA algorithm employed in the present study is given in Fig. 1.13.

Simulations were conducted on a Pentium 4, 3 GHz, 504 MB RAM computer, in the

MATLAB 7.0.1 environment. The optimization was repeated 20 times and the best

final solution among the 20 runs is chosen as proposed controller parameters. The best

final solutions obtained in the 20 runs for different FACTS controllers with various

input signal are given in Table 3.1

To evaluate the capability of the SVC, STATCOM and SSSC based

controllers on damping electromechanical oscillations of the example electric power

system, simulations are carried out. To assess the effectiveness and robustness of the

controllers, different loading conditions as given in Table 3.2 are considered.

Table 3.1: SSSC, STATCOM and SVC based controller’s parameters for SMIB

Controllers Signal/Parameters SK ST1 ST2 ST3 ST4

SSSC Remote (∆ω) 115.4319 1.0029 0.8153 1.1482 0.8128

STATCOM Remote (∆ω) 493.8315 1.4315 0.8985 0.0626 1.6768

SVC Remote (∆ω) 203.7043 0.2132 1.2849 1.0672 0.9910

SSSC Local (∆PL) 89.0582 1.3945 0.8498 0.4673 0.1650

STATCOM Local (∆PL) 346.2304 1.3837 1.3491 1.2812 1.7203

SVC Local (∆PL) 344.5442 1.0824 1.0124 0.9874 1.1058


73

Table 3.2: Operating conditions considered

Controllers Loading Conditions P (pu) δ0(deg.)

SSSC

STATCOM

SVC

Nominal 0.85 29.21

Light 0.5 55.52

Heavy 1 60.53

3.4.1 COMPARISON OF SVC, STATCOM AND SSSC BASED CONTROLLERS WITH REMOTE SIGNAL

A 3-phase fault is applied in the middle of transmission line at t=1sec and

cleared after 5-cycle under nominal loading condition. The variation of power angle δ,

speed deviation ∆ω and tie line power for the above contingency are shown in Figs.

3.6-3.8. It is clear from Figs. that when input to the controller is remote ∆ω, the

stability of the system are maintained with SVC, STATCOM and SSSC based

controllers and power system oscillations are effectively damped out. It can also be

seen from Figs. 3.6-3.8 STATCOM is slightly more effective than SVC from stability

point of view. It is also evident from Figs. 3.6-3.8 that best system response is

obtained with SSSC based damping controller.

0 1 2 3 4 5 6 7 8 9 10-6

-4

-2

0

2

4

6x 10

-3

Time (sec)

∆ω

(pu)

SVC STATCOM SSSC

Fig. 3.6 Speed deviation response for 5-cycle 3-phase fault in transmission line with nominal loading


74

0 1 2 3 4 5 6 7 8 9 1035

40

45

50

55

60

65

Time (sec)

δ (d

egre

e)

SVC STATCOM SSSC

Fig. 3.7 Power angle deviation response for 5-cycle 3-phase fault in transmission line with nominal loading

0 1 2 3 4 5 6 7 8 9 10400

600

800

1000

1200

1400

1600

1800

2000

2200

2400

Time (sec)

PL (

MW

)

SVC STATCOM SSSC

Fig. 3.8 Tie line power response 5-cycle 3-phase fault in transmission line with nominal loading

To test the robustness of designed controller different loading condition and

fault location is considered. A 5-cycle self clearing 3-phase fault is assumed near bus

3 at t=1.0 s under light loading condition. The system responses for the above

contingency are shown in Figs. 3.9-3.10. It is clear from the Figs. 3.9-3.10 that under

light loading condition best system response is obtained with SSSC-based

supplementary damping controller as the settling time is greatly reduced as compared

with SVC and STATCOM.


75

0 1 2 3 4 5 6 7 8 9 10-5

-4

-3

-2

-1

0

1

2

3

4

5x 10

-3

Time (sec)

∆ω (pu

)

SVC STATCOM SSSC

Fig. 3. 9 Speed deviation response for 5-cycle 3-phase fault in transmission line with light loading

0 1 2 3 4 5 6 7 810

15

20

25

30

35

40

45

Time (sec)

δ (d

egre

e)

SVC STATCOM SSSC

Fig. 3.10 Power angle deviation response for 5-cycle 3-phase fault in transmission line with light loading

The effectiveness of the proposed controllers is also tested under heavy

loading condition (given in Table 3.1) by applying a 5-cycle 3-phase fault disturbance

at Bus 2 which is cleared by tripping both lines. The system responses are shown in

Figs. 3.11-3.13. It can be seen from Figs. 3.11-3.13 that the proposed controllers are

robust and works effectively under various operating conditions. The best system

response is observed with SSSC controller compared to STATCOM and SVC

controllers.


76

0 1 2 3 4 5 6 7 8 9 10-8

-6

-4

-2

0

2

4

6

8

10x 10

-4

Time (sec)

∆ω (pu

)

SVC STATCOM SSSC

Fig. 3.11 Speed deviation response for 5-cycle 3-phase fault disturbance at Bus 2

cleared by both line tripping with heavy loading

0 1 2 3 4 5 6 7 8 9 1058.5

59

59.5

60

60.5

61

61.5

62

62.5

63

63.5

Time (sec)

δ (deg

ree)

SVC STATCOM SSSC

Fig. 3.12 Power angle deviation response for 5-cycle 3-phase fault disturbance at Bus 2 cleared by both line tripping with heavy loading

0 1 2 3 4 5 6 7 8 9 101750

1800

1850

1900

1950

2000

2050

2100

Time (sec)

PL (

MW

)

SVC STATCOM SSSC

Fig. 3.13 Tie line power response for 5-cycle 3-phase fault disturbance at Bus 2

cleared by both line tripping with heavy loading


77

3.4.2 COMPARISON OF SVC, STATCOM AND SSSC BASED CONTROLLERS WITH LOCAL SIGNAL

In order to verify the effectiveness of controllers with local input signal, the

performance of the SVC, STATCOM and SSSC with local line power deviation

( LP∆ ) input signal are tested for different loading conditions. The behavior of the

proposed controller is verified at nominal loading condition under severe disturbance

condition. A 5-cycle, 3-phase fault is applied at the middle of one transmission line

connecting bus 2 and bus 3, at t = 1.0 s. The fault is removed by opening the faulty

line and the lines are reclosed after 5-cycles. The system response under this severe

disturbance is shown in Figs. 3.14-3.16 where, the response with LP∆ -based SVC is

shown with dotted line, the response with proposed GSA optimized LP∆ -based

STATCOM dashed line and the response with LP∆ -based SSSC solid line. It is clear

that settling time and overshoots in case of LP∆ based SSSC based controller is

better than LP∆ based SVC and STATCOM controllers under nominal loading

condition.

0 1 2 3 4 5 6 7 8 9 10-8

-6

-4

-2

0

2

4

6

8x 10

-3

Time (sec)

∆ω (pu

)

SVC STATCOM SSSC



78

0 1 2 3 4 5 6 7 8 9 1035

40

45

50

55

60

65

70

Time (sec)

δ (d

egre

e)

SVC STATCOM SSSC

Fig. 3.15 Power angle deviation response 5-cycle 3-phase fault in transmission line with nominal loading

0 1 2 3 4 5 6 7 8 9 100

500

1000

1500

2000

2500

Time (sec)

PL (

MW

)

SVC STATCOM SSSC

Fig. 3.16 Tie line power response for 5-cycle 3-phase fault in transmission line with nominal loading

To test the robustness of the controller to the operating condition and type of

disturbance, the generator loading is changed to light loading condition as given in

Table 3.2. A 5-cycle self clearing 3-phase fault is assumed near bus 3 at t=1.0 s. The

system response under this contingency is shown in Figs. 3.17-3.18 which clearly

depict the robustness of the proposed controllers for changes in operating condition

and fault location. It can be seen from Figs. 3.17-3.18 that with the decrease in

loading condition, the performance of LP∆ -based SSSC controller is better than

LP∆ -based SVC and STATCOM based controllers.


79

0 1 2 3 4 5 6 7 8 9 10-6

-4

-2

0

2

4

6x 10

-3

Time (sec)

∆ω (pu

)

SVC STATCOM SSSC

Fig. 3.17 Speed deviation response for 5-cycle 3-phase in transmission line with light

loading

0 1 2 3 4 5 6 7 8 9 1010

15

20

25

30

35

40

45

Time (sec)

δ (d

egre

e)

SVC STATCOM SSSC

Fig. 3.18 Power angle deviation response for 5-cycle 3-phase fault in transmission

line with light loading

The effectiveness of the proposed controller is also tested at heavy loading

condition under small disturbance. The load near bus 2 is disconnected at t =1.0 s for

5-cycle. The response of speed deviation and power angle deviation for this case is

shown in Figs. 3.19 and 3.20 respectively. It is observed from Figs. 3.19 and 3.20 that

proposed LP∆ -based SSSC gives better system response thanLP∆ based SVC and

STATCOM controllers. It is also shown that settling times are greatly reduced with

LP∆ based SSSC controller compared to others.


80

0 1 2 3 4 5 6 7 8 9 10-8

-6

-4

-2

0

2

4

6

8x 10

-4

Time (sec)

∆ω (pu

)

SVC STATCOM SSSC

Fig. 3.19 Speed deviation response for 5-cycle 3-phase fault disturbance at Bus 2 cleared by both line tripping with heavy loading

0 1 2 3 4 5 6 7 8 9 1058.5

59

59.5

60

60.5

61

61.5

62

62.5

63

63.5

Time (sec)

δ (d

egre

e)

SVC STATCOM SSSC

Fig. 3.20 Power angle deviation response for 5-cycle 3-phase fault disturbance at Bus 2 cleared by both line tripping with heavy loading

3.4.3 COMPARISON OF CONTROLLERS WITH DIFFERENT SIGNALS In Section 3.4.1 and 3.4.2, a comparison is made between the SSSC,

STATCOM and SVC with both local and remote signals for stability enhancement of

the power system. It is observed that the SSSC based controller is more effective for

stability enhancement of the proposed system. In this Section, a comparison between

local and remote signal for SSSC based controller to improve the stability of power

system is carried out.


81

To assess the effectiveness and robustness of the proposed controller, three

different operating conditions as given in Table 3.2 are considered. The following

cases are considered

Case I: Nominal loading condition

The behavior of the proposed controller is verified at nominal loading condition

under severe disturbance condition. A 5-cycle, 3-phase self clearing fault is applied at

the middle of one transmission line connecting bus 2 and bus 3, at t = 1.0 s. The

system response under this severe disturbance is shown in Figs. 3.21-3.24 where, the

response without control (no control) is shown with dotted line, and the response with

proposed approach with local signal are considered is shown with dash line and time

delay with remote signal are considered with solid line respectively. For comparison,

it can be seen from Figs. 3.21-3.24 that when potential time delays are considered the

proposed approach remote signal is better than local signal.

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-8

-6

-4

-2

0

2

4

6

8x 10

-3

Time (sec)

∆ ω

(pu)

No control Local signal Remote signal



82

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 535

40

45

50

55

60

65

70

Time (sec)

δ (d

egre

e)

No control Local signal Remote signal

Fig. 3.22 Power angle deviation response for 5-cycle 3-phase fault in transmission line with nominal loading

0 0.5 1 1.5 2 2.5 3 3.5 40

500

1000

1500

2000

2500

Time (sec)

PL (

MW

)

No control

Local signal

Remote signal

Fig. 3.23 Tie line power response for the 5-cycle 3-phase fault in transmission line with nominal loading

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-0.2

-0.1

0

0.1

0.2

Time (sec)

Vq

(pu)

No control

Local signal

Remote signal

Fig. 3.24 Series injected voltage 5-cycle 3-phase fault in transmission line with nominal loading


83

Case II: Light loading condition

To test the robustness of the controller to the operating condition and type of

disturbance, the generator loading is changed to light loading condition as given in

Table 3.2. A 5-cycle 3-phase fault is assumed in one of the parallel transmission line

near bus 2 at t=1.0 s. The fault is cleared by tripping the faulted line and the lines are

reclosed after 5-cycles. The system response under this contingency is shown in Figs.

3.25-3.27 which clearly depicts the robustness of the proposed controller for changes

in operating condition and fault location. It can be seen that the proposed design

approach remote signal with time delays is better than local signal.

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-6

-4

-2

0

2

4

6x 10

-3

Time (sec)

∆ ω

(pu)

No control

Local signal

Remote signal

Fig. 3.25 Speed deviation response for 5-cycle 3-phase fault in transmission line with

light loading

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-500

0

500

1000

1500

2000

Time (sec)

PL (

MW

)

No control

Local signal

Remote signal

Fig. 3.26 Tie-line power flow response for 5-cycle 3-phase fault in transmission line

with light loading


84

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

Time (sec)

Vq

(pu)

No control

Local signal

Remote signal

Fig. 3.27 Series injected voltage Vq for 5-cycle 3-phase fault in transmission line with light loading

Case III: Heavy loading condition

The robustness of the proposed controller is also verified at heavy loading

condition under small disturbance by disconnecting the load near bus 1 at t =1.0 s for

100 ms with generator loading being changed to heavy loading condition. The system

response under this contingency is shown in Figs 3.28-3.29 from which it is clear that

the system is unstable without control under this severe disturbance and the stability

of the system is maintained with the proposed GSA optimized SSSC-based damping

controller.

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-1

-0.5

0

0.5

1x 10

-3

Time (sec)

∆ω (

pu)

No control

Local signalRemote signal

Fig. 3.28 Speed deviation response for 5-cycle 3-ph fault in transmission line with heavy loading


85

0 0.5 1 1.5 2 2.5 3 3.5 41400

1600

1800

2000

2200

Time (sec)

PL (

MW

)

No control

Local signal

Remote signal

Fig. 3.29 Tie-line power flow response for 5-cycle 3phase fault in transmission line with heavy loading

3.4.4 EFFECT OF SIGNAL TRANSMISSION DELAY To study the effect of variation in signal transmission delay on the

performance of controller, the transmission delay is varied and the response is shown

in Fig. 3.30. In this case, nominal loading condition with 5-cycle, 3-phase, self

clearing fault is assumed at the middle of one transmission line for the analysis

purpose. It is evident from Fig. 3.30 that the performances of the proposed controllers

are hardly affected by the signal transmission delays.

0 0.5 1 1.5 2 2.5 3 3.5 4-6

-4

-2

0

2

4

6x 10

-3

Time (sec)

∆ω (

pu)

Remote signal with 50 ms delay



Fig. 3.30 Speed deviation response showing for case of transmission delay


86

3.5 EXTENSION TO MULTI-MACHINE POWER SYSTEM WITH SSSC

3.5.1 SYSTEM UNDER STUDY The proposed approach of designing and optimizing the parameters of a SSSC

based damping controller is further extended to a multi-machine power system shown

in Fig. 3.31. It is similar to the power system used in references [73, 74]. The system

consists of three generators divided in to two subsystems and are connected via an

intertie. Following a disturbance, the two subsystems swing against each other

resulting in instability. To improve the stability the line is sectionalized and a SSSC is

assumed on the mid-point of the tie line. The relevant data for the system are given in

Appendix III. For remote input signal speed deviation of generator G1 and G3 is

chosen as the control input of SSSC based damping controller and for local signal real

power flow at the nearest bus (bus5) is selected.

G2

G3

G1

T2

T3

BUS2

BUS1

BUS3

BUS4

BUS5 BUS6

LOAD1

LOAD2

LOAD3

T1

L2

L3

L1

L1

L1

L1

LOAD4

SSSC

Fig. 3.31 Three machine power system with SSSC

Two distinct types of system oscillations are usually recognized in

interconnected power systems [78]. One is associated with units at a generating

station swinging with respect to rest of the power system. Such oscillations are

referred to as local mode of oscillations and have a frequency in the range of 0.8 to

2.0 Hz. The term local is used because the oscillations are localized at one power

plant. The second is associated with swinging of many machines in one part of the


87

system against machines in another part. These are inter area mode oscillations, and

have frequencies in the range of 0.2 to 0.7 Hz.

The objective functions J is defined as:

∫ ∑∑=

=⋅⋅∆+∆=

simtt

tIL dttJ

0)||||( ωω (3.5)

Where ∆ωI and ∆ωL are the speed deviations of inter-area and local modes of

oscillations respectively and tsim is the time range of the simulation. The same

approach as explained for SMIB case is followed to optimize the SSSC-based

damping controller parameters for three-machine case (i.e. for remote signal a delay

of 50 ms has been considered and for local signal the delay is neglected). The best

among the 20 runs for both the input signals are shown in Table 3.3.

Table 3.3: Optimization value of SSSC controller parameters in multi machine power system

Signal/Parameters SK ST1 ST2 ST3 ST4

Remote 148.8635 1.8085 0.4679 1.3291 1.1737

Local 140.2196 1.1676 0.9492 0.9657 0.8676

3.5.2 SIMULATIONS RESULTS

A self clearing 3-phase fault is applied near bus 1 at t = 1 s. The fault is

cleared after 5-cycles and the original system is restored after the fault clearance.

Figs. 3.32-3.34 show the variations of the inter-area and local mode of oscillation

against time respectively for both the control inputs. In these Figs., the response

without control (no control) is shown with dotted line; and responses with local signal

for SSSC-based controllers is shown with dashed line and the same with remote

signal is shown with solid line respectively. It is clear from Fig. 3.32 that inter-area

modes of oscillations are highly oscillatory in the absence of SSSC-based damping

controller and the proposed SSSC-based controller significantly improves the power


88

system stability by damping these oscillations with both local and remote signals.

However, remote signal seems to be a better choice compared to the local signal as

the power system oscillations are quickly damped out with remote signal.

To show the robustness of the proposed approach, another disturbance is

considered. The transmission line between bus 6 and bus 1 is tripped at t=1.0 sec and

reclosed after 5-cycles. The system response is shown in Figs. 3.35-3.36 from which

it is clear that remote signal with delay is a better choice than local signal for stability

improvement. For completeness, the load at bus 4 is disconnected for 100 ms and the

system response is shown in Figs. 3.37-3.38. It is clear from these Figs. that the

proposed controllers are robust and damps power system oscillations even under

small disturbance conditions. Further, the performance with remote speed deviation

signal is better than that with local signal.

0 2 4 6 8 10 12-10

-8

-6

-4

-2

0

2

4

6

8x 10

-3

Time (sec)

ω1- ω

3 (p

u)

No control

Local signal

Remote signal

Fig. 3.32 Inter-area mode of oscillation for 5-cycle 3-phase fault disturbance


89

0 2 4 6 8 10 12-5

0

5x 10

-3

Time (sec)

ω1- ω

2 (p

u)

No control

Local signal

Remote signal

Fig. 3.33 Local mode of oscillation for self clearing three phase fault disturbance

0 2 4 6 8 10 12-500

0

500

1000

1500

2000

2500

Time (sec)

PL (

MW

)

No control

Local signal

Remote signal

Fig. 3.34 Tie line power flow for self clearing three phase fault disturbance

0 2 4 6 8 10 12-3

-2

-1

0

1

2

3x 10

-3

Time (sec)

ω1- ω

3(pu

)

No control

Local signal

Remote signal

Fig. 3.35 Inter-area mode of oscillation for line outage disturbance


90

0 2 4 6 8 10 12-3

-2

-1

0

1

2x 10

-3

Time (sec)

ω2- ω

3 (p

u)

No control

Local signal

Remote signal

Fig. 3.36 Local mode of oscillation for line outage disturbance

0 2 4 6 8 10 12-4

-2

0

2

4

6x 10

-4

Time (sec)

ω1- ω

3 (p

u)

No control

Local signal

Remote signal

Fig. 3.37 Inter-area mode of oscillation for small disturbance

0 2 4 6 8 10 12-2

-1

0

1

2x 10

-4

Time (sec)

ω1- ω

2 (p

u)

No control

Local signal

Remote signal

Fig. 3.38 Local mode of oscillation for small disturbance


91

3.6 CONCLUSIONS

In this chapter, power system stability improvement by different FACTS

controllers namely SVC, STATCOM and SSSC based damping controllers is

thoroughly investigated. Both local and remote signals are considered. Speed

deviation of generator is taken as remote signal and line active power is taken as local

signal. For the controller design, appropriate time delays due to sensor time constant

and signal transmission delays are considered. The design problem is formulated as an

optimization problem and Gravitational Search Algorithm (GSA) is employed to

search for the optimal controller parameters. The performance of the proposed

controller is evaluated under different disturbances for both single-machine infinite

bus power system and multi-machine power system using both local and remote

signals. It is observed that STATCOM is slightly more effective than SVC from

stability point of view. It is also seen that best system response is obtained with SSSC

based damping controller. It is also noticed that the performance with remote speed

deviation signal is better than that with local signal for both single-machine infinite

bus power system and multi-machine power system.

comparison of different facts controllers and various...

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